1399 Software courses in Liverpool delivered Live Online

Duration 3 Days 18 CPD hours This course is intended for This course is most suited for IT professionals who have a need to understand the current requirements and core competences for managing IT in mission-critical environments. Overview After completion of the course the participant will be able to: 1. Provide guidance and implementation for IT strategy as set by senior IT and business management 2. Select and manage staff, implement training programs, career plan development and job rotation programs 3. Select, evaluate and negotiate vendors using RFI, RFP and selection criteria 4. Provide guidance for developing, testing and implementing business applications 5. Manage and/or assist in IT project management 6. Design and implement service management processes for incident, problem and change management 7. Understand the need for business continuity and design the business continuity plan 8. Review and implement information security practices and controls 9. Assist and initiate risk management practices 10. Understand and select new technologies such as cloud computing, big data, Internet of Things and social media to support business change demands 11. Select strategies for information management 12. Measure and improve quality of IT services CITS is designed to teach the skills, knowledge and competencies required of the modern IT specialist working at the senior professional, team-leader, supervisor or management level in IT management. IT Strategy The need for Information Technology Enterprise architecture Service catalogue Service level management Sustainable development IT Organisation Personnel need Roles and responsibilities Sourcing Selection process Hiring staff Managing staff Career planning Training / job rotation Performance appraisal Staff departures Vendor Selection / Management The importance of vendors Vendor selection Request For Information (RFI) Request For Proposal (RFP) Proposal evaluation Vendor reference checks Contract negotiation Contract management Vendor management Re-compete vendors Project Management Methodologies Project organisation Starting up / initiating Planning / initiation a project Risk Quality Scope Work / Product Breakdown Structure PERT diagram / Gantt chart Cost Communication Application Management Software Development Life Cycle (SDLC) Software Quality Assurance (SQA) Requirements Development Testing Adoption (implementation) Maintenance Service Management Incident management Problem management Change management Business Continuity Management Standards and guidelines Objectives Context Interested parties Scope Roles and responsibilities Resources and competences Awareness and communication Documentation Business Impact Analysis Risk Management Guidelines Context establishment Identification Analysis Evaluation Treatment Communication Monitoring and control Information Security Management Standards Confidentiality Integrity Availability Controls types Guideline for controls selection Control categories Information security awareness Security incident response Information and Knowledge Management Information management Data management Information management - technologies Business intelligence Data management - technologies Best practices in data governance Pitfalls in data governance Business Change Management Business change Frameworks, models and techniques Needs identification Cloud computing Social media / digital marketing Big data Internet of Things (IoT) Quality Management Standards, guidelines and frameworks Objectives Activities Services review Customer feedback Customer survey Key Performance Indicators (KPI) Metrics Scorecards and reports Quality register Exam Actual course outline may vary depending on offering center. Contact your sales representative for more information.

Duration 3 Days 18 CPD hours This course is intended for The primary audience for this course is an IT, facilities or data centre operations professional working in and around the data centre and having the responsibility to achieve and improve high-availability and manageability of the data centre. Overview After completion of the course the participant will be able to:? Understand the design life cycle of data centres and the stages involved? Discuss the data centre requirements in great level of detail with vendors, suppliers and contractors to ensure that these requirements are met? Validate design plans, quotes and offers proposed by vendors/contractors? Understand redundancy levels for both the data centre design/setup and maintenance? Understand the various building considerations such as bullet proofing, mitigation of seismic activity, fire ratings and thermal stability? Understand how to install a raised floor that meets requirements, avoiding misalignment, level differences and leakage? Understand how to read a Single Line Electrical Diagram to identify and avoid the most common design issues? Choose the correct UPS and parallel configuration, learn and avoid classic parallel installation mistakes? Understand how to calculate battery banks, validate offered configurations to ensure they meet requirements? Understand what distance to keep to avoid EMF issues for human safety and equipment disturbances? Understand the fundamental cooling setup, CFM, Delta-T and other important factors? Understand contamination factors and limitations? Understand full details of fire suppression options, how to calculate gas content and verify installations? Understand how to measure data centre energy efficiency and how to improve it The course will bring participants to the level of a suitable sparring partner with suppliers. They will be able to verify offers provided by vendors for correctness, effectiveness and efficiency. Data Centre Design/Life Cycle Overview Overview of the phases of a data centre life cycle Planning, re-alignment and continuous improvement Standards and Rating Level Definitions Rating level history Difference between Uptime and TIA-942 Rating level definitions Redundancy options (N+1), 2N, 2(N+1) Concurrent Maintainability/Compartmentalisation Example configurations Substation and feed requirements Maintenance options Operational processes guidelines/standards Skill development Building Considerations Building location considerations Floor and hanging loads requirements Fire rating for walls and glass Blast protection Bullet proofing Forced entry protection Advanced Raised Floor & Suspended Ceiling Raised floor installation guidelines Techniques to install a proper and leveled raised access floor Common mistakes Choosing the right tiles and their locations Seismic-mitigating floor constructions Choosing the correct suspended ceiling Advanced Power Power infrastructure layout; Formulas which you should know for the data centre Single Line Electrical diagrams; how to read to ensure key components are present for protection Over current protection devices (MCB/MCCB/VCB/ACB/Fuses) definitions and what to use where Earth Leakage devices (RCB/RCD/ELCB/GFCI/ALCI/RCBO), definitions and what to use where Sizing of protective components Lightning strikes and surge protection devices (TVSS/SPD), how they operate, where to use and how to install Power cabling and cable run considerations PDU/DB setup and minimum requirements Generators; Generator types: Standy/Prime/Continuous Component make up and functions Fuel storage and calculation Paralleling of gen-sets Generator room/area requirements UPS Systems; Required specifications for UPS systems How to read data sheets and select the correct UPS Requirements for parallel configurations and avoid pitfalls such as single point of failures How parallel installation should be done, classic mistakes made by installers and how to avoid these Harmonic Filters; Active/Passive filters and their application Battery Banks; Battery bank terminology Designing battery banks, how to calculate, and double check the battery bank to be installed Battery charging pitfalls and ensuring the right charger is being installed and used Using parallel battery banks; how to properly install them, limitations and risks when using batteries in parallel How to test batteries correctly and make decisions on cell/block or string replacement Battery casing choices; ABS, V0, V1, V2 Alternative energy storage; flywheel, re-usable cell, compressed air UPS, etc. Advanced Electro Magnetic Fields Sources of EMF Difference between single, three phase and bus-bar EMF Options available to measure EMF and how to interpret the results from single-axes and composite measurements Guidance on safe distance for equipment and humans Calculation of EMF attenuation factor for shielding material permeability and saturation factors Advanced Cooling Important definitions; dry-bulb, wet-bulb, dew-point, RH, sensible and latent heat Psychometric chart and ASHRAE recommendations Environmental class definitions and thermal specifications Temperature/humidity measurements guideline Heat dissipation methods Altitude impact on temperature intake to ICT equipment Floor plan setup for effective cooling Differences in tile surface and supporting structure and the air-flow performance impact Rack door construction and the flow performance impact Equipment Delta-T and its impact Optimising air flow Thermal units conversions Calculations for air volume displacement (CFM/CMH) Cooling capacity calculations Air-conditioning selection De- / humidifying options Air conditioning efficiency SHR impact on cost saving Efficiency indicator New cooling principle and techniques (Submerged, VSD/VRF/ECF/water- and air side economisers) Redundancy guidelines for air-conditioners avoiding classic misconceptions and mistakes for meeting ANSI/TIA-942 compliant designs Installation requirements Connections to fire panel and EPO Commissioning of air conditioners Set points and calibration CFD (Computational Fluid Dynamics) Advanced Fire Protection The fire triangle and elements to stop a fire Detection systems in detail (VESDA, VIEW, smoke sensors) Considerations for installation of sensors Proper testing of smoke sensors Water based systems i.e. deluge, wet-pipe, dry-pipe, pre-action and why most of them don't work and how to detect this Details on Inert and Halocarbon systems and how to select the correct system for your data centre How to calculate the gas content ensuring the appropriate level is installed to suppress the fire including safety considerations Other requirements for gas systems such as release times, hold times, pipe install requirements and other important factors Requirements for the fire detection panel Installation verification, methods, what to check and how New advanced fire suppression technologies Design and Install Scalable Networking Cabling System ANSI/TIA942 cabling structure topology ToR, EoR Design Intelligent patching systems Installation best practice such as routing, bending radius, separation from power, containment fill ratio, fiber link loss calculator, bonding and grounding requirement Standard for telecommunications labeling and administration Environmental Specifications and Contamination Control Acoustic noise effects, regulations, specifications and limits Data centre contaminations and classifications Measurements, standards and limits Preventive measures and avoidance Data Centre Efficiency Business drivers to go Green High-availability or Green? Green guidelines and standards How to measure it and what are acceptable numbers compared to the general industry PUE classes defined by Green Grid and issues with PUE Techniques for saving energy in all parts of the data centre i.e. application/system level, cooling, power distribution Mock ExamEXAM: Certified Data Centre Specialist

Duration 3 Days 18 CPD hours This course is intended for This course is geared for experienced Scala developers who are new to the world of machine learning and are eager to expand their skillset. Professionals such as data engineers, data scientists, and software engineers who want to harness the power of machine learning in their Scala-based projects will greatly benefit from attending. Additionally, team leads and technical managers who oversee Scala development projects and want to integrate machine learning capabilities into their workflows can gain valuable insights from this course Overview Working in a hands-on learning environment led by our expert instructor you'll: Grasp the fundamentals of machine learning and its various categories, empowering you to make informed decisions about which techniques to apply in different situations. Master the use of Scala-specific tools and libraries, such as Breeze, Saddle, and DeepLearning.scala, allowing you to efficiently process, analyze, and visualize data for machine learning projects. Develop a strong understanding of supervised and unsupervised learning algorithms, enabling you to confidently choose the right approach for your data and effectively build predictive models Gain hands-on experience with neural networks and deep learning, equipping you with the know-how to create advanced applications in areas like natural language processing and image recognition. Explore the world of generative AI and learn how to utilize GPT-Scala for creative text generation tasks, broadening your skill set and making you a more versatile developer. Conquer the realm of scalable machine learning with Scala, learning the secrets to tackling large-scale data processing and analysis challenges with ease. Sharpen your skills in model evaluation, validation, and optimization, ensuring that your machine learning models perform reliably and effectively in any situation. Machine Learning Essentials for Scala Developers is a three-day course designed to provide a solid introduction to the world of machine learning using the Scala language. Throughout the hands-on course, you?ll explore a range of machine learning algorithms and techniques, from supervised and unsupervised learning to neural networks and deep learning, all specifically crafted for Scala developers. Our expert trainer will guide you through real-world, focused hands-on labs designed to help you apply the knowledge you gain in real-world scenarios, giving you the confidence to tackle machine learning challenges in your own projects. You'll dive into innovative tools and libraries such as Breeze, Saddle, DeepLearning.scala, GPT-Scala (and Generative AI with Scala), and TensorFlow-Scala. These cutting-edge resources will enable you to build and deploy machine learning models for a wide range of projects, including data analysis, natural language processing, image recognition and more. Upon completing this course, you'll have the skills required to tackle complex projects and confidently develop intelligent applications. You?ll be able to drive business outcomes, optimize processes, and contribute to innovative projects that leverage the power of data-driven insights and predictions. Introduction to Machine Learning and Scala Learning Outcome: Understand the fundamentals of machine learning and Scala's role in this domain. What is Machine Learning? Machine Learning with Scala: Advantages and Use Cases Supervised Learning in Scala Learn the basics of supervised learning and how to apply it using Scala. Supervised Learning: Regression and Classification Linear Regression in Scala Logistic Regression in Scala Unsupervised Learning in Scala Understand unsupervised learning and how to apply it using Scala. Unsupervised Learning:Clustering and Dimensionality Reduction K-means Clustering in Scala Principal Component Analysis in Scala Neural Networks and Deep Learning in Scala Learning Outcome: Learn the basics of neural networks and deep learning with a focus on implementing them in Scala. Introduction to Neural Networks Feedforward Neural Networks in Scala Deep Learning and Convolutional Neural Networks Introduction to Generative AI and GPT in Scala Gain a basic understanding of generative AI and GPT, and how to utilize GPT-Scala for natural language tasks. Generative AI: Overview and Use Cases Introduction to GPT (Generative Pre-trained Transformer) GPT-Scala: A Library for GPT in Scala Reinforcement Learning in Scala Understand the basics of reinforcement learning and its implementation in Scala. Introduction to Reinforcement Learning Q-learning and Value Iteration Reinforcement Learning with Scala Time Series Analysis using Scala Learn time series analysis techniques and how to apply them in Scala. Introduction to Time Series Analysis Autoregressive Integrated Moving Average (ARIMA) Models Time Series Analysis in Scala Natural Language Processing (NLP) with Scala Gain an understanding of natural language processing techniques and their application in Scala. Introduction to NLP: Techniques and Applications Text Processing and Feature Extraction NLP Libraries and Tools for Scala Image Processing and Computer Vision with Scala Learn image processing techniques and computer vision concepts with a focus on implementing them in Scala. Introduction to Image Processing and Computer Vision Feature Extraction and Image Classification Image Processing Libraries for Scala Model Evaluation and Validation Understand the importance of model evaluation and validation, and how to apply these concepts using Scala. Model Evaluation Metrics Cross-Validation Techniques Model Selection and Tuning in Scala Scalable Machine Learning with Scala Learn how to handle large-scale machine learning problems using Scala. Challenges of Large-Scale Machine Learning Data Partitioning and Parallelization Distributed Machine Learning with Scala Machine Learning Deployment and Production Understand the process of deploying machine learning models into production using Scala. Deployment Challenges and Best Practices Model Serialization and Deserialization Monitoring and Updating Models in Production Ensemble Learning Techniques in Scala Discover ensemble learning techniques and their implementation in Scala. Introduction to Ensemble Learning Bagging and Boosting Techniques Implementing Ensemble Models in Scala Feature Engineering for Machine Learning in Scala Learn advanced feature engineering techniques to improve machine learning model performance in Scala. Importance of Feature Engineering in Machine Learning Feature Scaling and Normalization Techniques Handling Missing Data and Categorical Features Advanced Optimization Techniques for Machine Learning Understand advanced optimization techniques for machine learning models and their application in Scala. Gradient Descent and Variants Regularization Techniques (L1 and L2) Hyperparameter Tuning Strategies

AutoCAD Training for 15 hours - Live and Online The AutoCAD Training is for 15 hours that will cover from Introduction to Intermediate in small classes with only 1 people per class. AutoCAD course is for Windows or AutoCAD for MAC platforms. If you have AutoCAD for MAC, please let us know to book the specific course.  The training is tailored to your needs and we will focus the AutoCAD course on the area you want to learn.   During the training, you will receive many AutoCAD tips on how to work fast and efficient.  This live AutoCAD course will be now online at a reduced price.  You will receive a certificate of attendance at the end of the course. After the training, you can book 1 to 1 AutoCAD support to answer your questions and support your journey to learn AutoCAD. This is an extra service that you can book a minimum of 2.5 hours. Spread the cost with interest-free instalments. Buy now, pay later courses! AutoCAD Training: https://www.bimrevittraining.com/autocad-training AutoCAD Course Description AutoCAD Settings and Customization • Workspaces (AutoCAD Classic/2D Drafting & Annotation) • Background Color • Cross Air Size • New / Open and Save • User Preferences • Toolbars • Drawing Units • Drawing Limits • Snap Mode • Grid Display • Ortho Mode • Polar Tracking • Object Snap • Object Snap Tracking   AutoCAD Drawing Tools • Line • Multiple Line • Construction Line • Polyline • Polygon • Rectangle • Arc • Circle • Revision Cloud • Spline • Ellipse / Ellipse Arc • Insert Block • Make Block • Point • Hatch/Gradient • Region • Table • Multiline Text   Modify Tools • Erase • Copy • Mirror • Offset • Array • Move • Rotate • Scale • Stretch • Trim • Extend • Break at Point • Break • Join • Chamfer • Fillet • Explode   Working Methods •Object Properties •Match Properties •Layer Properties Manager •Adding Layers •Working with Layouts •External References •Insert/Edit Images •Insert PDF   AutoCAD Plotting / Publishing •Page Setup Manager •Plot Style Manager •Plotting •Publish •eTransmit

The NCSP® 800-53 Practitioner accredited (APMG International), certified (NCSC/GCHQ-UK), and recognized (DHS-CISA-USA) certification course teaches Digital Business, Operational Stakeholders, Auditors, and Risk Practitioners a Fast-Track approach to adopting and adapting the NIST Cybersecurity Framework and its 800-53 controls across an enterprise and its supply chain.The course also teaches candidates how to build a Digital Value Management System (DVMS) CPD overlay model capable of enabling the quick adoption and adaption of new frameworks and models (NIST-CSF, NIST Privacy Framework, CMMC, etc.) that may be required to address internal, external (regulatory), and cyber threat landscape changes. Finally, the course teaches candidates how to ensure the organization's DVMS is designed for use within the organization and auditable by government regulators looking to verify regulatory outcomes. The NCSP Practitioner 800-53 course is designed for both the Implementer and Auditor topics and participants select the exam they want to take (or an additional exam can be ordered to be certified as both an implementer and auditor).

Duration 3 Days 18 CPD hours This course is intended for This course is intended for security engineers, security architects, and information security professionals. Overview Identify security benefits and responsibilities of using the AWS Cloud Build secure application infrastructures Protect applications and data from common security threats Perform and automate security checks Configure authentication and permissions for applications and resources Monitor AWS resources and respond to incidents Capture and process logs Create and configure automated and repeatable deployments with tools such as AMIs and AWS CloudFormation This course demonstrates how to efficiently use AWS security services to stay secure in the AWS Cloud. The course focuses on the security practices that AWS recommends for enhancing the security of your data and systems in the cloud. The course highlights the security features of AWS key services including compute, storage, networking, and database services. You will also learn how to leverage AWS services and tools for automation, continuous monitoring and logging, and responding to security incidents. Prerequisites We recommend that attendees of this course have: Working knowledge of IT security practices and infrastructure concepts Familiarity with cloud computing concepts Completed AWS Security Essentials and Architecting on AWS courses 1 - Security on AWS Security in the AWS cloud AWS Shared Responsibility Model Incident response overview DevOps with Security Engineering 2 - Identifying Entry Points on AWS Identify the different ways to access the AWS platform Understanding IAM policies IAM Permissions Boundary IAM Access Analyzer Multi-factor authentication AWS CloudTrail 3 - Security Considerations: Web Application Environments Threats in a three-tier architecture Common threats: user access Common threats: data access AWS Trusted Advisor 4 - Application Security Amazon Machine Images Amazon Inspector AWS Systems Manager 5 - Data Security Data protection strategies Encryption on AWS Protecting data at rest with Amazon S3, Amazon RDS, Amazon DynamoDB Protecting archived data with Amazon S3 Glacier Amazon S3 Access Analyzer Amazon S3 Access Points 6 - Securing Network Communications Amazon VPC security considerations Amazon VPC Traffic Mirroring Responding to compromised instances Elastic Load Balancing AWS Certificate Manager 7 - Monitoring and Collecting Logs on AWS Amazon CloudWatch and CloudWatch Logs AWS Config Amazon Macie Amazon VPC Flow Logs Amazon S3 Server Access Logs ELB Access Logs 8 - Processing Logs on AWS Amazon Kinesis Amazon Athena 9 - Security Considerations: Hybrid Environments AWS Site-to-Site and Client VPN connections AWS Direct Connect AWS Transit Gateway 10 - Out-Of-Region Protection Amazon Route 53 AWS WAF Amazon CloudFront AWS Shield AWS Firewall Manager DDoS mitigation on AWS 11 - Security Considerations: Serverless Environments Amazon Cognito Amazon API Gateway AWS Lambda 12 - Threat Detection and Investigation Amazon GuardDuty AWS Security Hub Amazon Detective 13 - Secrets Management on AWS AWS KMS AWS CloudHSM AWS Secrets Manager 14 - Automation and Security by Design AWS CloudFormation AWS Service Catalog 15 - Account Management and Provisioning on AWS AWS Organizations AWS Control Tower AWS SSO AWS Directory Service

Duration 3 Days 18 CPD hours This course is intended for This course is intended for solutions architects, solution-design engineers, developers seeking an understanding of AWS architecting and individuals seeking the AWS Solutions Architect-Associate certification. Overview Identify AWS architecting basic practices. Explore using the AWS management tools: The AWS Console, Command Line Interface (CLI), and CloudFormation in a lab environment. Examine the enforcement of accounts security using policies. Identify the elements that build an elastic, secure, virtual network that includes private and public subnets. Practice building an AWS core networking infrastructure. Determine strategies for a layered security approach to Virtual Private Cloud (VPC) subnets. Identify strategies to select the appropriate compute resources based on business use-cases. Practice building a VPC and adding an Elastic Cloud Compute (EC2) instance in a lab environment. Practice installing an Amazon Relational Database Service (RDS) instance and an Application Load Balancer (ALB) in the VPC you created. Compare and contrast AWS storage products and services, based on business scenarios. Compare and contrast the different types of AWS database services based on business needs. Practice building a highly available, auto-scaling database layer in a lab. Explore the business value of AWS monitoring solutions. Identify the role of monitoring, event driven load balancing, and auto scaling responses, based on usage and needs. Identify and discuss AWS automation tools that will help you build, maintain and evolve your infrastructure. Discuss network peering, VPC endpoints, gateway and routing solutions based on use-cases. Discuss hybrid networking configurations to extend and secure your infrastructure. Discuss the benefits of microservices as an effective decoupling strategy to power highly available applications at scale. Explore AWS container services for the rapid implementation of an infrastructure-agnostic, portable application environment. Identify the business and security benefits of AWS serverless services based on business examples. Practice building a serverless infrastructure in a lab environment. Discuss the ways in which AWS edge services address latency and security. Practice building a CloudFront deployment with an S3 backend in a lab environment. Explore AWS backup, recovery solutions, and best practices to ensure resiliency and business continuity. Build a highly available and secure cloud architecture based on a business problem, in a project-based facilitator-guided lab. Architecting on AWS is for solutions architects, solution-design engineers, and developers seeking an understanding of AWS architecting. In this course, you will learn to identify services and features to build resilient, secure and highly available IT solutions on the AWS Cloud. Architectural solutions differ depending on industry, types of applications, and business size. AWS Authorized Instructors emphasize best practices using the AWS Well-Architected Framework, and guide you through the process of designing optimal IT solutions, based on real-life scenarios. The modules focus on account security, networking, compute, storage, databases, monitoring, automation, containers, serverless architecture, edge services, and backup and recovery. At the end of the course, you will practice building a solution and apply what you have learned with confidence. Prerequisites AWS Cloud Practitioner Essentials classroom or digital training, or Working knowledge of distributed systems Familiarity with general networking concepts Familiarity with IP addressing Working knowledge of multi-tier architectures Familiarity with cloud computing concepts 0 - Introductions & Course Map review Welcome and course outcomes 1 - Architecting Fundamentals Review AWS Services and Infrastructure Infrastructure Models AWS API Tools Securing your infrastructure The Well-Architected Framework Hands-on lab: Explore Using the AWS API Tools to Deploy an EC2 Instance 2 - Account Security Security Principals Identity and Resource-Based Policies Account Federation Introduction to Managing Multiple Accounts 3 - Networking, Part 1 IP Addressing Amazon Virtual Private Cloud (VPC), Patterns and Quotas Routing Internet Access Network Access Control Lists (NACLs) Security Groups 4 - Compute Amazon Elastic Cloud Compute (EC2) EC2 Instances and Instance Selection High Performance Computing on AWS Lambda and EC2, When to Use Which Hands-On Lab: Build Your Amazon VPC Infrastructure 5 - Storage Amazon S3, Security, Versioning and Storage Classes Shared File Systems Data Migration Tools 6 - Database Services AWS Database Solutions Amazon Relational Database Services (RDS) DynamoDB, Features and Use Cases Redshift, Features, Use Cases and Comparison with RDS Caching and Migrating Data Hands-on Lab: Create a Database Layer in Your Amazon VPC Infrastructure 7 - Monitoring and Scaling Monitoring: CloudWatch, CloudTrail, and VPC Flow Logs Invoking Events 8 - Automation CloudFormation AWS Systems Manager 9 - Containers Microservices Monitoring Microservices with X-Ray Containers 10 - Networking Part 2 VPC Peering & Endpoints Transit Gateway Hybrid Networking Route 53 11 - Serverless Architecture Amazon API Gateway Amazon SQS, Amazon SNS Amazon Kinesis Data Streams & Kinesis Firehose Step Functions Hands-on Lab: Build a Serverless Architecture 12 - Edge Services Edge Fundamentals Amazon CloudFront AWS Global Accelerator AWS Web Application Firewall (WAF), DDoS and Firewall Manager AWS Outposts Hands-On Lab: Configure an Amazon CloudFront Distribution with an Amazon S3 Origin 13 - Backup and Recovery Planning for Disaster Recovery AWS Backup Recovery Strategie Additional course details: Nexus Humans Architecting on AWS training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Architecting on AWS course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 3 Days 18 CPD hours This course is intended for The target audience for the SRE Practitioner course are professionals including: Anyone focused on large-scale service scalability and reliability Anyone interested in modern IT leadership and organizational change approaches Business Managers Business Stakeholders Change Agents Consultants DevOps Practitioners IT Directors IT Managers IT Team Leaders Product Owners Scrum Masters Software Engineers Site Reliability Engineers System Integrators Tool Providers Overview After completing this course, students will have learned: Practical view of how to successfully implement a flourishing SRE culture in your organization. The underlying principles of SRE and an understanding of what it is not in terms of anti-patterns, and how you become aware of them to avoid them. The organizational impact of introducing SRE. Acing the art of SLIs and SLOs in a distributed ecosystem and extending the usage of Error Budgets beyond the normal to innovate and avoid risks. Building security and resilience by design in a distributed, zero-trust environment. How do you implement full stack observability, distributed tracing and bring about an Observability-driven development culture? Curating data using AI to move from reactive to proactive and predictive incident management. Also, how you use DataOps to build clean data lineage. Why is Platform Engineering so important in building consistency and predictability of SRE culture? Implementing practical Chaos Engineering. Major incident response responsibilities for a SRE based on incident command framework, and examples of anatomy of unmanaged incidents. Perspective of why SRE can be considered as the purest implementation of DevOps SRE Execution model Understanding the SRE role and understanding why reliability is everyone's problem. SRE success story learnings This course introduces a range of practices for advancing service reliability engineering through a mixture of automation, organizational ways of working and business alignment. Tailored for those focused on large-scale service scalability and reliability. SRE Anti-patterns Rebranding Ops or DevOps or Dev as SRE Users notice an issue before you do Measuring until my Edge False positives are worse than no alerts Configuration management trap for snowflakes The Dogpile: Mob incident response Point fixing Production Readiness Gatekeeper Fail-Safe really? SLO is a Proxy for Customer Happiness Define SLIs that meaningfully measure the reliability of a service from a user?s perspective Defining System boundaries in a distributed ecosystem for defining correct SLIs Use error budgets to help your team have better discussions and make better data-driven decisions Overall, Reliability is only as good as the weakest link on your service graph Error thresholds when 3rd party services are used Building Secure and Reliable Systems SRE and their role in Building Secure and Reliable systems Design for Changing Architecture Fault tolerant Design Design for Security Design for Resiliency Design for Scalability Design for Performance Design for Reliability Ensuring Data Security and Privacy Full-Stack Observability Modern Apps are Complex & Unpredictable Slow is the new down Pillars of Observability Implementing Synthetic and End user monitoring Observability driven development Distributed Tracing What happens to Monitoring? Instrumenting using Libraries an Agents Platform Engineering and AIOPs Taking a Platform Centric View solves Organizational scalability challenges such as fragmentation, inconsistency and unpredictability. How do you use AIOps to improve Resiliency How can DataOps help you in the journey A simple recipe to implement AIOps Indicative measurement of AIOps SRE & Incident Response Management SRE Key Responsibilities towards incident response DevOps & SRE and ITIL OODA and SRE Incident Response Closed Loop Remediation and the Advantages Swarming ? Food for Thought AI/ML for better incident management Chaos Engineering Navigating Complexity Chaos Engineering Defined Quick Facts about Chaos Engineering Chaos Monkey Origin Story Who is adopting Chaos Engineering Myths of Chaos Chaos Engineering Experiments GameDay Exercises Security Chaos Engineering Chaos Engineering Resources SRE is the Purest form of DevOps Key Principles of SRE SREs help increase Reliability across the product spectrum Metrics for Success Selection of Target areas SRE Execution Model Culture and Behavioral Skills are key SRE Case study Post-class assignments/exercises Non-abstract Large Scale Design (after Day 1) Engineering Instrumentation- Instrumenting Gremlin (after Day 2)

Duration 2 Days 12 CPD hours This course is intended for This training is ideally suited for data analysts, IT professionals, and software developers who seek to augment their data processing and analytics capabilities. It will also benefit system administrators and data engineers who wish to harness Elastic Stack's functionalities for efficient system logging, monitoring, and robust data visualization. With a focus on practical application, this course is perfect for those aspiring to solve complex data challenges in real-time environments across diverse industry verticals. Overview This course combines engaging instructor-led presentations and useful demonstrations with valuable hands-on labs and engaging group activities. Throughout the course you'll explore: New features and updates introduced in Elastic Stack 7.0 Fundamentals of Elastic Stack including Elasticsearch, Logstash, and Kibana Useful tips for using Elastic Cloud and deploying Elastic Stack in production environments How to install and configure an Elasticsearch architecture How to solve the full-text search problem with Elasticsearch Powerful analytics capabilities through aggregations using Elasticsearch How to build a data pipeline to transfer data from a variety of sources into Elasticsearch for analysis How to create interactive dashboards for effective storytelling with your data using Kibana How to secure, monitor and use Elastic Stack's alerting and reporting capabilities The Elastic Stack is a powerful combination of tools for techniques such as distributed search, analytics, logging, and visualization of data. Elastic Stack 7.0 encompasses new features and capabilities that will enable you to find unique insights into analytics using these techniques. Geared for experienced data analysts, IT professionals, and software developers who seek to augment their data processing and analytics capabilities, Working with Elasticsearch will explore how to use Elastic Stack and Elasticsearch efficiently to build powerful real-time data processing applications. Throughout the two-day hands-on course, you?ll explore the power of this robust toolset that enables advanced distributed search, analytics, logging, and visualization of data, enabled by new features in Elastic Stack 7.0. You?ll delve into the core functionalities of Elastic Stack, understanding the role of each component in constructing potent real-time data processing applications. You?ll gain proficiency in Elasticsearch for distributed searching and analytics, Logstash for logging, and Kibana for compelling data visualization. You?ll also explore the art of crafting custom plugins using Kibana and Beats, and familiarize yourself with Elastic X-Pack, a vital extension for effective security and monitoring. The course also covers essentials like Elasticsearch architecture, solving full-text search problems, data pipeline building, and creating interactive Kibana dashboards. Learn how to deploy Elastic Stack in production environments and explore the powerful analytics capabilities offered through Elasticsearch aggregations. The course will also touch upon securing, monitoring, and utilizing Elastic Stack's alerting and reporting capabilities. Hands-on labs, captivating demonstrations, and interactive group activities enrich your learning journey throughout the course. Introducing Elastic Stack What is Elasticsearch, and why use it? Exploring the components of the Elastic Stack Use cases of Elastic Stack Downloading and installing Getting Started with Elasticsearch Using the Kibana Console UI Core concepts of Elasticsearch CRUD operations Creating indexes and taking control of mapping REST API overview Searching - What is Relevant The basics of text analysis Searching from structured data Searching from the full text Writing compound queries Modeling relationships Analytics with Elasticsearch The basics of aggregations Preparing data for analysis Metric aggregations Bucket aggregations Pipeline aggregations Substantial Lab and Case Study Analyzing Log Data Log analysis challenges Using Logstash The Logstash architecture Overview of Logstash plugins Ingest node Visualizing Data with Kibana Downloading and installing Kibana Preparing data Kibana UI Timelion Using plugins

Duration 1 Days 6 CPD hours This course is intended for This course is intended for students who want to learn basic Word 2021 skills, such as creating, editing, and formatting documents; inserting simple tables and creating lists; and employing a variety of techniques for improving the appearance and accuracy of document content. Overview In this course, you will learn fundamental Word skills. You will: Navigate and perform common tasks in Word, such as opening, viewing, editing, saving, and printing documents, and configuring the application. Format text and paragraphs. Perform repetitive operations efficiently using tools such as Find and Replace, Format Painter, and Styles. Enhance lists by sorting, renumbering, and customizing list styles. Create and format tables. Insert graphic objects into a document, including symbols, special characters, illustrations, pictures, and clip art. Format the overall appearance of a page through page borders and colors, watermarks, headers and footers, and page layout. Use Word features to help identify and correct problems with spelling, grammar, readability, and accessibility. These days, most people take electronic word processing for granted. While we may still write out our grocery lists with pen and paper, we expect to use a computer to create the majority of our documents. It's impossible to avoid word-processing software in many areas of the business world. Managers, lawyers, clerks, reporters, and editors rely on this software to do their jobs. Whether you are an executive secretary or a website designer, you'll need to know the ins and outs of electronic word processing. Microsoft© Word 2021 is designed to help you move smoothly through the task of creating professional-looking documents. Its rich features and powerful tools can make your work easy, and even fun. In this course, you'll learn how to use Word 2021 to create and edit simple documents; format documents; add tables and lists; add design elements and layout options; and proof documents. This course covers Microsoft Office Specialist Program exam objectives to help you prepare for the Word Associate (Office 365 and Office 2021): Exam MO-100 and Word Expert (Office 365 and Office 2021): Exam MO-101 certifications. Getting Started with Word 2021 Topic A: Navigate in Microsoft Word Topic B: Create and Save Word Documents Topic C: Manage Your Workspace Topic D: Edit Documents Topic E: Preview and Print Documents Topic F: Customize the Word Environment Formatting Text and Paragraphs Topic A: Apply Character Formatting Topic B: Control Paragraph Layout Topic C: Align Text Using Tabs Topic D: Display Text in Bulleted or Numbered Lists Topic E: Apply Borders and Shading Working More Efficiently Topic A: Make Repetitive Edits Topic B: Apply Repetitive Formatting Topic C: Use Styles to Streamline Repetitive Formatting Tasks Managing Lists Topic A: Sort a List Topic B: Format a List Adding Tables Topic A: Insert a Table Topic B: Modify a Table Topic C: Format a Table Topic D: Convert Text to a Table Inserting Graphic Objects Topic A: Insert Symbols and Special Characters Topic B: Add Images to a Document Controlling Page Appearance Topic A: Apply a Page Border and Color Topic B: Add Headers and Footers Topic C: Control Page Layout Topic D: Add a Watermark Preparing to Publish a Document Topic A: Check Spelling, Grammar, and Readability Topic B: Use Research Tools Topic C: Check Accessibility Topic D: Save a Document to Other Formats